Monday, 11 November 2013

machine learning--01 : linear regression and batch gradient descent

Linear regression is one of the famous machine learning algorithm.This algorithm assume the relationship between the input(features) and the output(targets) are linear, it use a hypothesis to predict the result.

Equation 1 is the hypothesis we use to predict the results, usually we define X0 as 1.To find out the parameters, we could use batch gradient descent.

Since the square error produce by linear regression only has one minimum value(it is a convex), we don't need to worry about the starting point.You could find more details on this website. Implement this algorithm with the help of openCV is pretty simple(octave/matlab even more simpler).